Major tech companies are no longer content with encouraging employees to experiment with AI. They are tracking adoption, building it into performance reviews and, in some cases, refusing to hire candidates who can’t demonstrate AI fluency.
According to a recent Wall Street Journal report, companies ranging from 300-person start-ups to giants like Amazon, Google, Meta, Microsoft and Salesforce have moved into active enforcement mode. Google is factoring AI use into software engineer performance reviews for the first time this year. Meta has overhauled its review system to do the same, tracking how many lines of code engineers produce with AI assistance.
The enforcement push is not surprising given what the data shows about voluntary adoption. Deloitte’s 2026 State of AI in the Enterprise report, based on a survey of more than 3,200 business and IT leaders, found that while worker access to AI tools expanded 50% in a single year, fewer than 60% of employees with access actually use AI in their daily workflow. Companies gave people the tools. Many didn’t pick them up.
At Conductor, a 300-person digital marketing firm, CEO Seth Besmertnik describes his response as “carrots and sticks,” according to WSJ reporting. The company built an AI competency scoring system that rates employees from one to five, with top scores going to those who create AI-powered workflows that improve outcomes for their colleagues.
What AI enforcement means for HR
The measurement problem is thornier than it looks. Tracking whether employees use AI tools is relatively straightforward. Measuring whether they use them well is not. Lines of code written with AI assistance say little about quality, strategic thinking or the judgment required to know when AI output needs correction. HR teams will need rubrics that distinguish genuine fluency from surface-level compliance.
There are also equity and legal risks that deserve attention. AI tools are not equally accessible or intuitive across every role. Employees with limited tech backgrounds and those in functions where AI applications are still nascent may face different adoption challenges than engineers at well-resourced firms.
Employment attorneys warn that tying performance reviews to AI proficiency or adoption rates risks disparate impact discrimination against protected groups under Title VII and the ADEA. Age discrimination concerns are especially prominent, as research documents stark generational gaps in AI comfort levels. Employers should audit these metrics to mitigate bias, according to guidance from employment law firm Ogletree Deakins.
Read more: Why CHROs must redefine performance in 2026
Key word: training
Here is the tension at the center of this story: Companies are mandating AI use while simultaneously failing to redesign work around it. The Deloitte report found that 84% of organizations have not restructured jobs or workflows around AI capabilities, even as insufficient worker skills rank as the top barrier to AI integration.
General Assembly’s State of Tech Talent 2026, based on a survey of 500 HR leaders, found that 83% now believe company success depends more on upskilling existing employees for AI than on hiring new talent. Yet the same survey identified low employee buy-in and low leadership buy-in as the top barriers to training programs actually taking hold.
“The AI skills gap is growing too fast for companies to hire their way out,” said Daniele Grassi, CEO of General Assembly, in a release. He said that increasing investment in upskilling reflects that leaders understand that existing employees bring the necessary business context, institutional knowledge and cultural navigation skills. “Continuous, incremental and role-specific learning is the only way to keep up with the pace of technology change.”
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